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Record W6996665875

Social Taboo And New Worlds: Resilience of Identity Facing Ecological and Cultural Crisis

2022· article· en· W6996665875 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTunneling and Rock Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousTabooMainstreamCultural systemPsychological resilienceCultural identityClimate changeEcological systems theoryAdaptation (eye)Ecological anthropology
DOInot available

Abstract

fetched live from OpenAlex

Environmental media and literature have become increasingly fascinated with the future changes society and mainstream culture might face. As the world faces anthropogenic climate change and ecological disaster, the existential systems of Indigenous peoples provide examples of modern adaptation and change, through remaining true to cultural valuing and their systems of ecological management. The practices surrounding taboo provide frameworks for establishing environmental considerations and societal worldviews. Through the analysis of the case studies of the Pueblo, Inuit, and Tagbanuwa, a social relationship with nature can be identified, which when broken turns into cultural and ecological consequences. These cultural structures and norms, in turn, generate methods of repair and punishment, with cultural healing occurring through acts such as banishment or ceremonies. The breaking of ecological and cultural frameworks due to climate stress or cultural assimilation results in narratives shifting towards explaining consequences resulting in environmental disaster through the lens of apocalypse and revitalization. The hope of survival and the cultural systems that promote Indigenous resilience generate the idea of new identities for the impacted communities, as their emerging culture forms around adaptation and the reimagined world left to them. With these frameworks in mind, modern environmental ethics concerning climate change might be formed from the incorporation of Indigenous media for those directly affected by these pressures, as social tools taking an early step towards the future with current actions of adaptation and resilience.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0140.056
Scholarly communication0.0140.016
Open science0.0020.017
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.252
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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